This project combines game theory and genetic algorithms in a simulation model for evolutionary learning and strategic behavior. It is often observed in the real world that strategic scenarios change over time, and deciding agents need to adapt to new information and environmental structures. Yet, game theory models often focus on static games, even for dynamic and temporal analyses. This simulation model introduces a heuristic procedure that enables these changes in strategic scenarios with Genetic Algorithms. Using normalized 2x2 strategic-form games as input, computational agents can interact and make decisions using three pre-defined decision rules: Nash Equilibrium, Hurwicz Rule, and Random. The games then are allowed to change over time as a function of the agent’s behavior through crossover and mutation. As a result, strategic behavior can be modeled in several simulated scenarios, and their impacts and outcomes can be analyzed, potentially transforming conflictual situations into harmony.

The model constructs a complex network of traffic based on the main urban area of Zhengzhou, China, and simulates the urban rainfall process using the ABM model to analyse the real-time risk of flooding hazards in the nodes of the complex network.

This model is designed for the paper of “Bustle Changes the City - Facility for Stopping off and Modeling Urban Dynamics -“. And all experimental results in the paper were implemented in this model.

The Bronze Age Collapse model (BACO model) is written using free NetLogo software v.6.0.3. The purpose of using the BACO model is to develop a tool to identify and analyse the main factors that made the Late Bronze Age and Early Iron Age socio-ecological system resilient or vulnerable in the face of the environmental aridity recorded in the Aegean. The model explores the relationship between dependent and independent variables. Independent variables are: a) inter-annual rainfall variability for the Late Bronze Age and Early Iron Age in the eastern Mediterranean, b) intensity of raiding, c) percentage of marine, agricultural and other calorie sources included in the diet, d) soil erosion processes, e) farming assets, and d) storage capacity. Dependent variables are: a) human pressure for land, b) settlement patterns, c) number of commercial exchanges, d) demographic behaviour, and e) number of migrations.

PPHPC is a conceptual model for studying and evaluating implementation strategies for spatial agent-based models (SABMs). It is a realization of a predator-prey dynamic system, and captures important SABMs characteristics.

The Agent-Based Wildfire Simulation Environment (ABWiSE) translates the concept of a moving fire front as a set of mobile fire agents that respond to, and interact with, vegetation, wind, and terrain. Presently, the purpose of ABWiSE is to explore how ABM, using simple interactions between agents and a simple atmospheric feedback model, can simulate emergent fire spread patterns.

An agent-based model designed as a tool to assess and plan free-ranging dog population management programs that implement Animal Birth Control (ABC). The time, effort, financial resources and conditions needed to successfully control dog populations and achieve rabies control can be determined by performing virtual experiments using DogPopDy.

The Relation-Based Model (RBM) purpose is to operationalise (a form of) process-relational (PR) thinking to serve as a thinking tool for process-relational thinking among social-ecological system (SES) researchers. The development of this model itself has been a ‘Proof of concept’- exercise to see whether we actually represent process-relational thinking in a methodology that is entity-based (ABM).

The target of the agent-based model is to show the emergence, change and disappearance of fishing assemblages (focusing on processes of self-organisation) in a Mexican fishery using a process-relational view. From this view, a fishery is regarded as an assemblage in which fishing can be enabled, fishing can occur, and fish can be bought/sold. These core doings - or sub-assemblages or capacities - maintain the assemblage. Each (sub)assemblage reflects different actualisations of constellations of relations and elements (buyers, fishers, fuel, permits, vessels and wind). The RBM thereby reflects an artificial fishery in which agents (elements) and their links (relations) engage in (enabling) fishing and buying/selling.

Using data from the British Social Attitude Survey, we develop an agent-based model to study the effect of social influence on the spread of meat-eating behaviour in the British population.

The model proposes a translation of some Luhmann’s concepts (social sub-system, perturbation, dissipation, social communication and power) into a model using a stylized spatial-society as a metaphor of a Luhmann’s social subsystem. The model has been used to improve the social theory understanding and to evaluate the effect of different parameterization in the global stabilization and individual/social power distribution.